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» Using classifier ensembles to label spatially disjoint data
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ICCV
2009
IEEE
13 years 3 months ago
Fast realistic multi-action recognition using mined dense spatio-temporal features
Within the field of action recognition, features and descriptors are often engineered to be sparse and invariant to transformation. While sparsity makes the problem tractable, it ...
Andrew Gilbert, John Illingworth, Richard Bowden
ETRA
2000
ACM
199views Biometrics» more  ETRA 2000»
13 years 9 months ago
Identifying fixations and saccades in eye-tracking protocols
The process of fixation identification--separating and labeling fixations and saccades in eye-tracking protocols--is an essential part of eye-movement data analysis and can have a...
Dario D. Salvucci, Joseph H. Goldberg
IJCV
2006
161views more  IJCV 2006»
13 years 5 months ago
Discriminative Random Fields
In this research we address the problem of classification and labeling of regions given a single static natural image. Natural images exhibit strong spatial dependencies, and mode...
Sanjiv Kumar, Martial Hebert
MLDM
2007
Springer
13 years 11 months ago
Transductive Learning from Relational Data
Transduction is an inference mechanism “from particular to particular”. Its application to classification tasks implies the use of both labeled (training) data and unlabeled (...
Michelangelo Ceci, Annalisa Appice, Nicola Barile,...
ICCV
2003
IEEE
14 years 7 months ago
Space-time Interest Points
Local image features or interest points provide compact ract representations of patterns in an image. In this paper, we propose to extend the notion of spatial interest points int...
Ivan Laptev, Tony Lindeberg